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SYNTHESYS NAD: Providing itinerary related datasets and tools (for integration, visualisation and quality check)

The funtion of this service is to detect itinerary patterns in georeferenced primary data presumably collected during a collecting event.

BioCLIM

BIOCLIM utilizes a boxcar environmental envelope algorithm to identify locations that have environmental conditions that fall within the environmental range recorded for present occurrences. Specifically the minimum and maximum values for each environmental predictor are identified to define the multidimensional environmental box where the element is known to occur. Study area sites that hale environmental conditions within the boundaries of the multidimensional box are predicted as potential sites of occupancy. Uses presence occurrence data only.

 
Software available with DIVA GIS.

DOMAIN

Uses a point-to-point similarity metric (Gower metric) to assign a classification value to a potential site based on its proximity in environmental space to the most similar positive occurrence location. Similarity between the site of interest and each of recorded present occurrence location is calculated by summing the standardized distance between the two points for each predictor variable. The standardization is achieved by dividing the distance by the predictor variable range for the presence sites, equalizing the contribution from each predictor variable. The standardized distance is subtracted from 1 to obtain the complementary similarity.

A practical guide to geostatistical mapping of environmental variables

Geostatistical mapping can be defined as analytical production of maps by using field observations, auxiliary information and a computer program that calculates values at locations of interest. Today, increasingly the heart of a mapping project is, in fact, the computer program that implements some (geo)statistical algorithm to a given point data set. Purpose of this guide is to assist you in producing quality maps by using fully-operational tools, without a need for serious additional investments.

Biodiverse

Biodiverse is a tool for the spatial analysis of diversity using indices based on taxonomic, phylogenetic and matrix-based (e.g. genetic distance) relationships, as well as related environmental and temporal variations. Biodiverse supports four processes: (1) linked visualisation of data distributions in geographic, taxonomic, phylogenetic and matrix spaces; (2) spatial moving window analyses including richness, endemism, phylogenetic diversity and beta diversity; (3) spatially constrained agglomerative cluster analyses; and (4) randomisations for hypothesis testing. Biodiverse is open-source and supports user developed extensions.

Diversity Workbench

The Diversity Workbench is work in progress, aiming at developing a set of information models and application components that collaborate through agreed software interfaces. That is, each component of the Workbench applications uses services from other applications, but at the same time does not need to know about the internal design and implementation of them (encapsulation principle). The goal is increased reuse and collaboration across project and national borders.

The Mycology.Net

The Mycology.Net has been established as a non-commercial scientific data platform for linking mycological and lichenological websites in a structured way.

The Mycology.Net aims to

The Phycology.Net

The Phycology.Net has been established as a non-commercial scientific data platform for linking phycological websites in a structured way. The Phycology.Net aims to

* provide access to online data on the biodiversity of algae, especially their taxonomy, distribution, phylogeny, descriptive characters, collections, literature etc.

LIAS – A Global Information System for Lichenized and Non-Lichenized Ascomycetes

LIAS is a multi-authored information system for the collection and distribution of descriptive and other biodiversity data on lichens and non-lichenized ascomycetes. The goal is

* to provide a working space for cooperation and collaboration of experts on ascomycetes in the Internet

Ecological Niche Modeling (ENM)

The workflow offers an extensible framework for analyzing or predicting the impact of environmental changes on the distribution of biodiversity. Especially in combination with data aggregation workflows like the Taxonomic Data Refinement Workflow (DRW), the ENM workflows facilitate the analysis of species distribution patterns over large geo-temporal, taxonomic, and environmental scales. Examples for applications are studies of species adaptations to climate change, dynamic modeling of ecologically related species, identification of regions with accumulated risk for invasion, potential for restoration, or natural protected areas.

ENM Statistical Workflow (ESW)

The ENM statistic workflow (ESW) allows the computation of the extent and intensity of change in species potential distribution through computation of the differences between two raster layers using the R statistical environment (R Core Team 2013). The difference file is computed from two input files (in this case present projection and 2050 projection). The difference between each corresponding raster cell value is computed and stored in the difference file, regardless of the input files’ geographical extent and origin.

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